- A
Embed all fields in a single document and rely on automatic indexing
Why wrong: Automatic indexing may not optimize for specific query patterns. A composite index on the filtered field is more efficient.
- B
Normalize the data by storing locale in a separate container and use cross-container queries
Why wrong: Cross-container queries in Cosmos DB are expensive and not recommended for frequent filtering on a single field.
- C
Define a fixed schema for all documents to ensure every document has the locale field
Why wrong: Cosmos DB is schema-agnostic; forcing a fixed schema with nullable fields doesn't improve indexing performance.
- D
Create a composite index that includes the locale field
A composite index on the locale field (and optionally including other fields) allows the query engine to quickly locate matching documents, reducing RU consumption and improving response time.
Quick Answer
The correct approach is to create a composite index that includes the locale field. This works because Azure Cosmos DB uses the composite index to directly locate documents matching the filter, avoiding a full scan of every document. Since locale is a sparse field—present in only about 30% of profiles—the composite index efficiently narrows the search to relevant documents, significantly reducing query RU costs. On the DP-900 exam, this tests your understanding of how indexing strategies impact performance for sparse data, a common scenario in real-world NoSQL workloads. A frequent trap is assuming a default index suffices for all queries, but sparse fields benefit from targeted composite indexes that combine the filter field with the partition key or sort order. Remember the tip: “Sparse fields need composite shields”—composite indexes act as a shield against expensive scans by pre-organizing the data for fast lookups.
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
This DP-900 practice question tests your understanding of describe considerations for working with non-relational data on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A mobile gaming company stores player profiles in Azure Cosmos DB. Each profile document contains many optional fields, and queries frequently filter by the player's locale (a field present in about 30% of documents). Which approach will optimize query performance for these filters?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Create a composite index that includes the locale field
Option D is correct because creating a composite index that includes the locale field allows Azure Cosmos DB to efficiently filter queries by locale without scanning every document. Since locale is present in only 30% of documents, a composite index reduces the query RU cost by directly locating matching documents, leveraging the index's sorted structure for faster lookups.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Embed all fields in a single document and rely on automatic indexing
Why it's wrong here
Automatic indexing may not optimize for specific query patterns. A composite index on the filtered field is more efficient.
- ✗
Normalize the data by storing locale in a separate container and use cross-container queries
Why it's wrong here
Cross-container queries in Cosmos DB are expensive and not recommended for frequent filtering on a single field.
- ✗
Define a fixed schema for all documents to ensure every document has the locale field
Why it's wrong here
Cosmos DB is schema-agnostic; forcing a fixed schema with nullable fields doesn't improve indexing performance.
- ✓
Create a composite index that includes the locale field
Why this is correct
A composite index on the locale field (and optionally including other fields) allows the query engine to quickly locate matching documents, reducing RU consumption and improving response time.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume automatic indexing is sufficient for all queries, but they overlook that sparsely populated fields benefit from explicit composite indexing to avoid high RU costs from index scans.
Detailed technical explanation
How to think about this question
Composite indexes in Azure Cosmos DB store multiple fields in a single index entry, enabling efficient queries that filter on multiple properties or a single property with high selectivity. Under the hood, the index is a B-tree structure that allows point lookups and range scans; for a field like locale present in 30% of documents, a composite index can reduce query RU from potentially thousands to single digits by avoiding full document scans. In real-world scenarios, this is critical for high-throughput gaming applications where player profile queries must be fast and cost-effective.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe considerations for working with non-relational data on Azure — This question tests Describe considerations for working with non-relational data on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a composite index that includes the locale field — Option D is correct because creating a composite index that includes the locale field allows Azure Cosmos DB to efficiently filter queries by locale without scanning every document. Since locale is present in only 30% of documents, a composite index reduces the query RU cost by directly locating matching documents, leveraging the index's sorted structure for faster lookups.
What should I do if I get this DP-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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